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A number of effective classification algorithms have been developed for spoken language recognition, and it has been a common practice in the NIST Language Recognition Evaluations (LREs) that an information fusion is applied to boost the performance of the recognition system. This paper investigates the fusion of multiple output scores generated using different classifiers that complement to further...
This paper presents the development of the speech, text and pronunciation dictionary resources required to build a large vocabulary speech recognizer for the Malay language. This project is a collaboration project among three universities: USM, MMU from Malaysia and NTU from Singapore. The Malay speech corpus consists of read speech (speaker independent/ dependent and accent independent/ dependent)...
This paper presents a new strategy for designing the parallel phone recognizers for spoken language recognition. Given a collection of parallel phone recognizers, we select a subset of phones from each phone recognizer for each target language to construct a target-oriented phone tokenizer (TOPT). As a result, the collection of target-oriented phone tokenizers is more effective than the original parallel...
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